Hardware / Cloud Requirements
Requirements for Single Server / Virtual Machine
For simplicity and cost-effectiveness, you can run FormX.ai on a single server/virtual machine.
Minimum Specification:
- 16 Core Intel CPU (each core must be at least 2.6Ghz or faster)
- 32GB RAM
- 120GB SSD
- GPU: RTX 5090 (32GB VRAM)
Requirements for Kubernetes Cluster
Here are the minimum specifications:
| Purposes | Number of Instances | Minimal Specification |
|---|---|---|
| API / Extraction Workers | 3 VMs (minimal for Kubernetes) | 8 vCPU 16GB RAM 30GB SSD |
Database (PostgreSQL) (Using managed PostgreSQL is recommended) |
| 4 vCPU 8GB RAM 64GB SSD |
| Self-Hosted OCR (Optional) |
| 8 vCPU 16GB RAM 30GB SSD |
Self-Hosted and Fine-Tune LLM Model
|
| 4 vCPU
|
ML Workers for dataset generation
| 3 VMs | 8 vCPU 16GB RAM 100GB+ SSD |
ML Trainer for model training
| 1 VM (more for parallel training) | 8 vCPU 16GB RAM 100GB+ SSD GPU: P100 or better 16GB+ vRAM |
Storage
| 10GBs+ (depends on image size) |
Cloud Resources Inventories
For a typical Cloud Deployment, here are the list of Cloud Resources Required:
| Inventory | Purposes | Related Cloud Products |
|---|---|---|
| Kubernetes | Run the applications, workers, trainers | GCP GKE Azure AKS AWS EKS |
| Database | Store the configs, audit logs, temporarily result for async requests | GCP Cloud SQL for PostgreSQL Azure Database for PostgreSQL AWS RDS for PostgreSQL |
| Image Storage | Storage of the images for training (optional) | Google Cloud Storage Azure Blob Storage AWS S3 |
| OCR | OCR | Google Vision API Azure OCR |
| Other Software Components | Redis: Cache authentication tokens Authgear: For authentication | Using some pods on the k8s cluster |